SOTAVerified

Relational Reasoning

The goal of Relational Reasoning is to figure out the relationships among different entities, such as image pixels, words or sentences, human skeletons or interactive moving agents.

Source: Social-WaGDAT: Interaction-aware Trajectory Prediction via Wasserstein Graph Double-Attention Network

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 161–170 of 483 papers

TitleStatusHype
Learning to Coarsen Graphs with Graph Neural Networks—0
Does Entity Abstraction Help Generative Transformers Reason?—0
A Critical Review of Inductive Logic Programming Techniques for Explainable AI—0
Graph Collaborative Reasoning—0
CORE-Text: Improving Scene Text Detection with Contrastive Relational ReasoningCode1
COMPOSER: Compositional Reasoning of Group Activity in Videos with Keypoint-Only ModalityCode1
Concept Representation Learning with Contrastive Self-Supervised Learning—0
Variational Deep Logic Network for Joint Inference of Entities and Relations—0
Systematic Generalization with Edge TransformersCode1
Joint Modeling of Visual Objects and Relations for Scene Graph Generation—0
Show:102550
← PrevPage 17 of 49Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1CTP A4 Hops0.99—Unverified